Unseen Wounds: PTSD Among Search and Rescue Teams Responding to the February 6, 2023 Earthquake in Türkiye

Abstract

In terms of occupational health and safety, psychosocial risks in the workplace can lead to temporary or permanent harm. Search and rescue workers assisting earthquake victims may develop PTSD due to the trauma they experience and witness. This study estimates the prevalence of PTSD among search and rescue workers involved in the February 6, 2023, earthquake in Türkiye. This study utilized the PTSD Checklist for DSM-5 (PCL-5) to assess 619 individuals. The results showed that the earthquake significantly affected post-traumatic stress symptoms across all demographic groups. Female participants (x̄ = 2.43) exhibited higher stress levels than male participants (x̄ = 2.24), showing an 8.48% difference. Participants with higher education levels (x̄ = 2.34) showed more stress than those with lower education (x̄ = 1.67). Individuals with over a decade of experience (x̄ = 3.28) experienced more distress compared to those with less than three years of experience (x̄ = 2.83). Participants under 30 (x̄ = 2.30) were more affected than those over 50 (x̄ = 2.25). Firsthand experience of the earthquake (x̄ = 2.49) resulted in greater distress compared to learning about it through communication channels (x̄ = 2.01). Concerning PTSD symptoms, 191 participants (30.86%) scored 33 or higher, which indicates clinically significant PTSD. Among the participants, 22 experienced severe to extremely severe symptoms, with 19 showing extremely severe symptoms on at least one subscale, 3 displaying extremely severe symptoms across all four subscales, and 9 demonstrating extremely severe symptoms in three subscales.

1. Introduction

Throughout their lives, individuals encounter various man-made and natural conditions that lead to stress, whose intensity and occurrence are steadily rising over time [1]. This growing threat is evident from the large volume of documents and heightened research interest. For example, stress and stress-related trauma have become a focal point for researchers over the past decade, accounting for 66.33% (20,590 out of 31,040) of publications in the SCOPUS database (as of June 4, 2024). To reveal the core content of these studies, we constructed a co-occurrence network (Figure 1), which highlights prominent trauma-related topics such as cultural trauma [2], holocaust [3], migration [4], refugee [5], identity [6], historical trauma [7], racism [8], narrative [9], violence and sexual violence [10], war [11], and ethics [12]. These topics are often associated with diverse physiological and biochemical disturbances [13]. Stress, depression, resilience, substance use, and mental health are key parameters discussed, with adolescents, children, and youth being major focus groups. While trauma linked to natural disasters is less thematically represented, some reports address this topic, particularly earthquakes [14,15].

Seismic movements caused by the sudden release of energy along fault lines are known as “earthquakes,” one of the most devastating natural disasters globally. Türkiye, situated in a tectonically active zone, frequently experiences shallow earthquakes. On February 6, 2023, a doublet earthquake with epicenters in Kahramanmaraş and Elbistan caused catastrophic destruction across ten provinces, resulting in over 50,000 deaths, more than 100,000 injuries, and significant cultural losses [16]. According to AFAD [16], the earthquakes had magnitudes of 7.7 and 7.6, while USGS [17] reported seven large earthquakes within 11 h, including magnitudes of 7.8, 6.7, and 7.5. American seismologist Harold Tobin [18] stated that since instrumental seismic measurements began in the 20th century, this is the first time two large earthquakes of such magnitude have occurred within 24 h. Consequently, the February 6 earthquake is described as the “disaster of the century” due to its scale and impact [19,20,21,22,23,24,25].

The disaster profoundly affected not only the direct victims but also the 60,217 professionals and volunteers involved in search and rescue operations, including public institutions, NGOs, security units, local teams, and international groups. Disaster workers face significant psychological risks, with common symptoms such as post-traumatic stress, secondary trauma, and indirect traumatization [26,27,28]. Other issues, including depression, anxiety disorders, and substance dependency, may also arise [29]. Responses to trauma vary based on event severity and individual perceptions, influenced by factors such as psychiatric history, childhood trauma, coping strategies, and genetic predispositions [30]. Personality traits, particularly psychological resilience, play a crucial role in the development of secondary traumatic stress symptoms [31].

Professional search and rescue work is considered one of the most stressful occupations, with conditions that can cause both physiological and psychological effects. A resilient mindset is essential for coping with severe or chronic stress, and training programs have been shown to help maintain psychological balance by enhancing personal strengths, stress management, problem-solving, and conflict resolution skills [32]. Increasing work demands, trauma exposure, and technology-related pressures contribute to widespread psychological distress among workers. In this context, the present study aims to assess the psychological states of rescue workers following the February 6 earthquake.

We aimed to reveal how demographic factors of research and rescue professionals are influential in terms of stress experienced after the earthquake. In this context, a series of statistical analyses were employed to reveal the stress levels of rescue workers, varying by age, education, and experience, under destructive and challenging conditions.

2. Materials and Methods

2.1. Study Design and Participants

In June 2023, around four months after the earthquake struck southern Turkey, a cross-sectional survey including a sample of 619 people was conducted. Participation was voluntary. The participants were AFAD personnel who participated in search and rescue missions after the earthquake on February 6. Purposive sampling was used, focusing on those who were formally listed as members of the search and rescue response team by the Disaster and Emergency Management Authority (AFAD). The research team obtained a contact list from AFAD. A total of 4000 people were chosen at random and contacted through internal message platforms and email, among other institutional communication methods. The online survey platform was equally accessible to everyone who was contacted. However, individual consent and willingness to fill out the survey were prerequisites for participation. As a result, we recognize the possibility of sample bias as a limitation, as also further noted in the limitations section of the present study. Daniel and Cross’s recommendations [33] were used to calculate the sample size for the participants. The sample size (n) was calculated according to the formula given below:

n = [z² * p * (1 − p)/e²]/[1 + (z² * p * (1 − p)/(e² * N))]

where z = 1.96 for a confidence level (α) of 95%, p = proportion (0.15), N = population size 60,217, and e = margin of error, 0.05 [33]

• z = 1.96, p = 0.15, N = 60,217, e = 0.05
• n ≥ [1.96² * 0.15 * (1 − 0.15)/0.05²]/[1 + (1.96² * 0.15 * (1 − 0.15)/(0.05² * 60,217))]
• n ≥ 195.9216/1.0033 = 195.286
• n ≈ 196
• The sample size (with finite population correction) was equal to 196.

2.2. Demographic Information of the Participants

A total of 619 search and rescue workers took part in this study (

Table 1. Demographic data.

		Frequency	Percent	Cumulative Percent
Age
	17–24	148	23.90	23.90
	25–29	105	16.96	40.28
	30–39	146	23.58	64.45
	40–49	159	25.68	90.14
	50 and over	61	9.85	100
Gender
	Male	480	77.54
	Female	139	22.46
Education
	Primary school	4	0.64	0.64
	Secondary school	10	1.61	2.26
	High school	99	15.99	18.25
	Vocational school	71	11.47	29.72
	Bachelor’s	393	63.48	93.21
	Master’s and higher	42	6.78	100
Experience
	0–3 years	285	46.04	46.04
	3–5 years	57	9.20	55.25
	5–10 years	42	6.78	62.03
	10 years and over	235	37.96	100

). The age distribution of the participants is as follows: 148 individuals (23.90%) were aged 17 to 24, 105 individuals (16.96%) were aged 25 to 29, and 146 individuals (23.5%) were aged 30 to 39. Additionally, 159 participants (25.68%) were between 40 and 49 years old, and 61 participants (9.85%) were 50 years old or older. Regarding gender, 480 participants (77.54%) were male, while 139 participants (22.46%) were female.

Regarding educational status, 63.48% (393 individuals) were university graduates, 6.78% (42 individuals) held a master’s degree, 11.47% (71 individuals) were vocational school graduates, 15.99% (99 individuals) were high school graduates, 1.62% (10 individuals) were middle school graduates, and 0.64% (4 individuals) were elementary school graduates. In terms of experience as search and rescue workers, 46.04% (285 individuals) had 0–3 years of experience, 9.20% (57 individuals) had 3–5 years of experience, 6.78% (42 individuals) had 5–10 years of experience, and 37.96% (235 individuals) had over 10 years of experience. Considering all data (

Table 2. Descriptive statistics.

Categories	N	Min.	Max.	M	SD	V	S	K
Age	619	17	70	34.66	10.67	113.99	0.32	−0.94
Gender	619	1	2	1.22	0.41	0.17	1.32	−0.25
Education	619	1	6	4.56	0.93	0.87	−1.13	0.92
Experience	619	1	4	2.37	1.38	1.91	0.86	−1.82

M: mean, SD: standard deviation, V: variance, S: skewness, K: kurtosis.

), the participants’ ages ranged from 17 to 70 years, with a mean age of 34.66 (±10.67). The average gender distribution was 1.22 (±0.41), the average education level was 4.56 (±0.93), and the average experience was 2.37 (±1.38).

2.3. Ethical Principles of Research

Ethics committee approval for this study was obtained from the Scientific Research and Publication Board of Iğdır University on June 6, 2024, under the reference number E-37077861-900-139707. The questions were administered online, and participating search and rescue workers received comprehensive online information regarding the study’s purpose and methodology, with a clear emphasis on the voluntary nature of their participation.

2.4. Data Collection Tools

Participants completed the Posttraumatic Stress Disorder (PTSD) Checklist for DSM-5 (PCL-5) [34]. They were first provided with a demographic information form and the checklist (PCL). The PCL is one of the most widely used self-report tools for assessing PTSD [35]. Developed by the National Center in 1990, it consists of twenty items that align with PTSD symptom criteria. Participants rated the extent to which each PTSD symptom affected them over the past month on a 5-point Likert scale.

The PCL-5, which was employed in this investigation, has been psychometrically verified in Turkey and has already undergone linguistic and cultural adaptation. To guarantee semantic and conceptual equivalency, the adaptation procedure involved forward and reverse translation, expert panel evaluation, and pilot testing. The Turkish version of the PCL-5 has good construct validity, convergent validity, and internal consistency across a range of Turkish populations, according to studies by Boysan et al. (2017) [35]. As a result, this version was thought to be appropriate for evaluating PTSD symptoms among Turkish search and rescue personnel.

Since the questions in the PCL-5 survey closely match the diagnostic criteria for PTSD as outlined in the DSM-5-TR, this survey can be used to make a provisional diagnosis of PTSD. In the DSM-5, a PTSD diagnosis is assessed based on four symptom clusters, which are measured through four subscales in the PCL-5 survey. These four symptom clusters including criteria B-E are re-experiencing, avoidance, negative alterations in cognition and mood, and hyperarousal (

Table 3. PCL-5 rating scale of symptoms.

Criteria	Questions	Normal	Mild	Moderate	Severe	Extremely Severe
Re-experience (B)	1–5	x̄ ≥ 1.23	1.23 < x̄ ≤ 1.64	1.64 < x̄ ≤ 2.455	2.455 < x̄ ≤ 3.265	x̄ > 3.265
Avoidance (C)	6–7
Negative Alterations (D)	8–15
Hyperarousal (E)	19–20

). The PCL-5 survey assesses each of these symptom clusters, gauging the severity and occurrence of PTSD symptoms, which allows for a provisional PTSD diagnosis.

Following the recommendations of the researchers who developed the scale, a reliability analysis was performed on the scale using the data gathered in this study. The Cronbach’s alpha internal consistency coefficients for the subscales of the scale were calculated and the results are as follows: 0.926 for the re-experiencing subscale, 0.941 for the avoidance subscale, 0.921 for the negative alterations subscale, and 0.917 for the hyperarousal subscale. Reliability coefficients of 0.70 and above indicate that the scale is considered “reliable” [36]. Based on these results, it can be said that all subscales of the PCL-5 PTSD scale are reliable for the measurements to be conducted (

Table 4. Cronbach’s alpha internal consistency coefficients for the subscales.

Item-Total Statistics
	Scale Mean If Item Deleted	Scale Variance If Item Deleted	Corrected Item-Total Correlation	Cronbach’s Alpha If Item Deleted
Re-experiencing	48.5089	1145.852	0.791	0.926
Avoidance	52.8255	1094.788	0.740	0.941
Negative Alterations	53.8223	1183.784	0.822	0.921
Hyperarousal	52.1680	1128.836	0.838	0.917
Total Average Score	51.6672	1129.828	0.990	0.893

).

2.5. Statistical Analysis

This study examined the extent to which post-traumatic stress disorder levels in search and rescue workers following the earthquake could be predicted. The data were analyzed using SPSS 27.0 software. First, the data underwent checks for missing and erroneous entries, followed by univariate and multivariate outlier analysis. For the sub-questions of the research, the normality of the data was taken into account when comparing stress disorders based on socio-demographic characteristics. In this study, the Skewness and Kurtosis coefficients were examined to assess normality, ensuring they fell within the range of ±1. If these coefficients fell within the ±1 tolerance range, the data were considered to follow a normal distribution. Consequently, parametric analysis techniques were employed for comparisons between groups. In this context, independent samples t-tests and one-way analysis of variance (ANOVA) were used for group comparisons. When the relevant group had two sub-levels, the independent samples t-test was applied, and for three or more sub-levels, one-way ANOVA was utilized.

In the comparisons related to the gender variable, which is one of the socio-demographic characteristics in this study, the independent samples t-test was applied since the variable consisted of two sub-levels (male, female). One-way ANOVA was applied to variables such as age (17–24, 25–29, 30–39, 40–49, and 50 and above), professional seniority (0–3 years, 3–5 years, 5–10 years, and over 10 years), and educational levels (elementary school, middle school, high school, vocational school, undergraduate, and graduate) since these variables had three or more sub-levels.

For the variables where one-way ANOVA was applied, Tukey post hoc and Scheffe Bonferroni tests were used to identify which pairs of groups had significant differences. These tests were chosen because the variance among the groups was homogeneous. The Kolmogorov–Smirnov (Lilliefors Significance Correction) and Shapiro–Wilk normality tests indicated that all values were below 99.99%, confirming a significantly normal distribution.

Furthermore, the current data were analyzed using the LISREL 8.80 [37] and PLS-SEM 2.4 toolboxes [38] software. The LISREL analysis is performed by selecting the parameters of a model through maximum likelihood estimation (MLE), determining the parameters that best fit the observed data to the statistical model used. On the other hand, PLS-SEM toolbox is based on partial least squares (PLS) regression and, rather than finding maximum variance hyperplanes between response and independent variables, it creates a linear regression model by projecting the estimated variables and observable variables into a new space. The data obtained from both analyses were evaluated for model fit according to recommended guidelines and cutoff values [39,40]. In particular, fit statistics derived from the absolute fit class measure the extent to which the model reproduces sample variances and covariances through the chi-square value. Smaller values in this statistic indicate better fit. Theoretically, the p-value for chi-square should not be statistically significant as it would indicate no significant difference between observed relationships among variables and those implied by the estimated model. However, in practice, even with large sample sizes, p-values for chi-square can be significant even with relatively small differences between observed and estimated models. Other indices from the absolute fit class such as Standardized Root Mean Square Residual (SRMR) are used to focus on average discrepancies between correlations in observed data and those predicted by the model. SRMR values <0.08 indicate good model fit. We evaluated these fitness statistics using an approach based on noncentral chi-squared distribution that mitigates model complexity for metrics like SRMR, indicating good fitness at <0.06 [41]. Finally, we also used the Tucker-Lewis Index (TLI), or Non-Normed Fit Index along with the Comparative Fit Index (CFI), which incorporates a penalty function to add freely estimated parameters that do not significantly improve fit. Both TLI and CFI are comparative fit statistics that evaluate a specified solutions adequacy compared to a more restricted nested baseline model generally compared against a null model. Values approaching 1 indicate improved fitness; values >0.90 suggest adequate fitness, while values >0.95 are considered indicative of good model fit. Effect size measures were calculated to assess the practical significance of the findings. For independent samples t-tests, Cohen’s d values were reported, and for ANOVA analyses, partial eta squared (η²) values were used. Cohen’s d values were interpreted as small (0.2), medium (0.5), and large (0.8); η² values were interpreted as small (0.01), medium (0.06), and large (0.14) effects, following established guidelines [42,43].

In addition to covariance-based SEM, PLS-SEM analysis was also conducted to ensure robustness of the model, particularly due to indications of non-normality in the dataset. While SEM (via LISREL) was used to examine theoretical model fit through maximum likelihood estimation, PLS-SEM served as a complementary method, which is better suited for data that deviate from normality and for models with relatively complex latent structures [44,45]. Our aim was not to compare model performance directly but to validate structural relationships using both parametric and non-parametric estimation techniques. This dual approach helped confirm the internal consistency of the proposed PTSD model under different statistical assumptions.

3. Results

A variance analysis was conducted to evaluate the impact of demographic and experience-related variables on post-traumatic stress symptoms and post-traumatic growth, which are critical outcomes given the traumatic conditions faced by search and rescue workers. The analysis showed that experiencing the earthquake had a significant overall effect on post-traumatic stress symptoms, regardless of age, education, gender, or experience (

Table 5. Item-level descriptive statistics for the PCL-5.

Questionnaire	Mean ± SD (IC95%)	M If Item Removed	V If Item Removed	Item–Total Correlation	α If Item Removed
1. Repeated, disturbing, and unwanted memories of the stressful experience?	2.19 ± 1.214	42.72	245.981	0.647	0.938
2. Repeated, disturbing dreams of the stressful experience?	2.35 ± 1.220	43.35	245.808	0.649	0.938
3. Suddenly feeling or acting as if the stressful experience were actually happening again (as if you were actually back there reliving it)?	2.58 ± 1.264	43.13	243.249	0.692	0.937
4. Feeling very upset when something reminded you of the stressful experience?	3.33 ± 1.189	42.38	249.381	0.568	0.939
5. Having strong physical reactions when something reminded you of the stressful experience (for example, heart pounding, trouble breathing, sweating)?	1.86 ± 1.075	43.85	247.781	0.685	0.938
6. Avoiding memories, thoughts, or feelings related to the stressful experience?	2.34 ± 1.196	43.36	245.183	0.681	0.938
7. Avoiding external reminders of the stressful experience (for example, people, places, conversations, activities, objects, or situations)?	2.04 ± 1.188	43.67	245.540	0.676	0.938
8. Trouble remembering important parts of the stressful experience?	1.89 ± 1.039	43.82	255.668	0.462	0.941
9. Having strong negative beliefs about yourself, other people, or the world (for example, having thoughts such as: I am bad, there is something seriously wrong with me, no one can be trusted, the world is completely dangerous)?	1.86 ± 1.109	43.85	252.104	0.533	0.940
10. Blaming yourself or someone else for the stressful experience or what happened after it?	1.95 ± 1.156	43.76	251.298	0.531	0.940
11. Having strong negative feelings such as fear, horror, anger, guilt, or shame?	2.22 ± 1.217	43.48	244.855	0.677	0.938
12. Loss of interest in activities that you used to enjoy?	2.39 ± 1.256	43.32	244.687	0.658	0.938
13. Feeling distant or cut off from other people?	2.24 ± 1.290	43.47	242.078	0.707	0.937
14. Trouble experiencing positive feelings (for example, being unable to feel happiness or have loving feelings for people close to you)?	2.12 ± 1.227	43.59	243.543	0.707	0.937
15. Irritable behavior, angry outbursts, or acting aggressively?	2.24 ± 1.239	43.47	243.382	0.703	0.937
16. Taking too many risks or doing things that could cause you harm?	1.85 ± 1.107	43.85	251.135	0.563	0.940
17. Being “super alert” or watchful or on guard?	2.85 ± 1.299	42.86	244.899	0.628	0.939
18. Feeling jumpy or easily startled?	2.24 ± 1.248	43.46	242.544	0.721	0.937
19. Having difficulty concentrating?	2.13 ± 1.173	43.58	243.445	0.745	0.936
20. Trouble falling or staying asleep?	2.22 ± 1.268	43.49	244.257	0.662	0.938

Re-experiencing: green; Avoidance: yellow; Negative alterations: blue; Hyperarousal: orange.

). Women (x̄ = 2.43) exhibited significantly higher levels of post-traumatic stress compared to men (x̄ = 2.24), with a difference of 8.48%. Participants with higher education levels (x̄ = 2.34) reported notably greater stress symptoms than those with lower education (x̄ = 1.67). Interestingly, individuals with over 10 years of experience in search and rescue work experienced higher levels of distress compared to those with less than 3 years of experience (mean scores 2.37 and 2.24, respectively). A comparison across age groups revealed that workers under the age of 30 (x̄ = 2.30) were more affected than those over 50 (x̄ = 2.25). Moreover, search and rescue workers who were physically present during the earthquake (x̄ = 2.49) exhibited significantly greater distress than those who learned of the event through communication channels and later joined the site (x̄ = 2.01) (Table 5).

This study found that participants in the 17–24 age group (x̄ = 2.4) felt significantly more distant or disconnected from others compared to those in the 40–49 age group (x̄ = 2.01). Similarly, the 17–24 age group (x̄ = 2.47) had greater difficulty falling asleep or staying asleep compared to the 40–49 age group (x̄ = 1.97).

Women (x̄ = 2.68) experienced more disturbing recurring dreams after the earthquake compared to men (x̄ = 2.26). They also reported a higher rate of suddenly reliving the earthquake (x̄ = 2.81) compared to men (x̄ = 2.51). Furthermore, women (x̄ = 3.51) felt more upset than men (x̄ = 3.28) when reminded of the earthquake by any event.

Furthermore, women (x̄ = 2.53) experienced significantly more negative emotions such as fear, anger, guilt, or shame after the earthquake compared to men (x̄ = 2.14). Women (x̄ = 2.73) also reported a greater sense of indifference toward activities they previously enjoyed, as well as a stronger perception of distance and detachment from others compared to men (x̄ = 2.60). The findings indicated that women had more difficulty experiencing positive emotions, with mean scores (x̄ = 2.33) notably higher than those of men (x̄ = 2.06). Women also had greater trouble concentrating after the trauma compared to men (x̄ = 2.32 vs. 2.08). In addition, women reported more difficulty falling asleep and staying asleep (x̄ = 2.45 vs. 2.15).

Among search and rescue workers, those with a bachelor’s degree (x̄ = 3.13) experienced the feeling of re-living the earthquake more intensely compared to those with a high school diploma (x̄ = 2.61). Additionally, bachelor’s degree holders exhibited avoidance behaviors in situations that reminded them of the earthquake (x̄ = 2.13) significantly more frequently than high school graduates (x̄ = 1.79).

Furthermore, associate degree holders (x̄ = 2.54) reported feeling significantly more distant and detached from others compared to high school graduates (x̄ = 1.99). This study also revealed that individuals with more than 10 years of search and rescue experience (x̄ = 3.28) experienced the feeling of reliving the earthquake more intensely than those with less than 3 years of experience (x̄ = 2.83). Additionally, participants with over 10 years of experience (x̄ = 2.03) showed stronger physical reactions to reminders of the earthquake compared to those with less than 3 years of experience (x̄ = 1.76). This group also exhibited more avoidance behaviors related to memories and feelings about the earthquake (x̄ = 2.55) than those with less than 3 years of experience (x̄ = 2.24). Furthermore, participants with over 10 years of experience (x̄ = 2.10) were more likely to report a tendency to blame themselves or others after stressful experiences compared to those with less than 3 years of experience (x̄ = 1.85) (

Table 6. p values for each group and the reliability.

PCL-5 Item	Age	Gender	Education	Experience	Inform.
1(B1)	0.122	0.110	0.002 **	0.000 ***	0.000 ***
2(B2)	0.239	0.000 ***	0.125	0.413	0.014 *
3(B3)	0.201	0.014 *	0.062	0.395	0.000 ***
4(B4)	0.079	0.043 *	0.219	0.171	0.203
5(B5)	0.643	0.270	0.179	0.010 *	0.203
6(C1)	0.563	0.254	0.074	0.006 **	0.000 ***
7(C2)	0.262	0.098	0.049 *	0.067	0.052
8(D1)	0.938	0.778	0.226	0.224	0.034 *
9(D2)	0.907	0.602	0.654	0.174	0.033 *
10(D3)	0.672	0.525	0.053	0.024 *	0.356
11(D4)	0.810	0.001 ***	0.111	0.723	0.039 *
12(D5)	0.328	0.000 ***	0.610	0.723	0.000 ***
13(D6)	0.010 *	0.000 ***	0.038 *	0.195	0.013 *
14(D7)	0.667	0.020 *	0.149	0.267	0.012 *
15(E1)	0.825	0.227	0.473	0.085	0.000 ***
16(E2)	0.649	0.305	0.147	0.001 ***	0.002 **
17(E3)	0.791	0.934	0.323	0.363	0.032 *
18(E4)	0.280	0.163	0.284	0.400	0.000 ***
19(E5)	0.069	0.034 *	0.250	0.429	0.002 **
20(E6)	0.011 *	0.017 *	0.370	0.338	0.008 **

* p < 0.05, ** p < 0.01 *** p < 0.001; B: re-experienced, C: avoidance, D: negative alterations, E: hyperarousal.

).

On the other hand, participants with 3–5 years of experience (x̄ = 1.51) reported taking fewer risks compared to those with 0–3 years of experience (x̄ = 1.75). Conversely, those with more than 10 years of experience (x̄ = 2.02) reported significantly higher risk-taking behaviors. Participants who personally experienced the earthquake (x̄ = 3.25) reported reliving the earthquake more frequently than those who repeatedly performed rescue operations (x̄ = 3.08), those who heard about the earthquake from relatives (x̄ = 2.82), and those who learned about it through communication channels (x̄ = 2.46). Moreover, participants who experienced the earthquake (x̄ = 2.56) reported having more recurring dreams related to the event compared to those who learned about it through communication channels (x̄ = 2.08). Those who had directly experienced the earthquake (x̄ = 3.02), those informed due to their work (x̄ = 2.47), those who heard from relatives (x̄ = 2.33), and those who learned through communication channels (x̄ = 2.27) were also more likely to report sudden re-experiencing of the earthquake.

Additionally, participants who experienced the earthquake (x̄ = 2.23) reported reacting more strongly on a physical level when reminded of the event compared to those informed through their job (x̄ = 1.74) and those who learned about it through communication channels (x̄ = 1.56). They also reported greater difficulty remembering important details of the earthquake (x̄ = 1.96) compared to those who received news through other channels (x̄ = 1.15). This group (x̄ = 2.04) developed more negative beliefs about themselves and the world than those who learned about the earthquake through communication channels (x̄ = 1.64). Participants who experienced the earthquake (x̄ = 2.37) also reported stronger negative emotions, such as fear, anger, guilt, or shame, compared to those who learned about it through communication channels (x̄ = 1.94) (Table 6).

Furthermore, those who experienced the earthquake (x̄ = 2.71) reported a greater decrease in interest toward activities they previously enjoyed compared to those informed through their job (x̄ = 2.21) and those who learned through communication channels (x̄ = 2.18). Participants who directly experienced the earthquake (x̄ = 2.42) also expressed feeling more distant and disconnected from others compared to those who learned about it through communication channels (x̄ = 2.08).

Participants who directly experienced the earthquake (x̄ = 2.30) reported having greater difficulty experiencing positive emotions compared to those who learned about it through communication channels (x̄ = 1.81). These participants (x̄ = 2.47) also exhibited more extreme irritability, anger outbursts, or aggressive behavior after the earthquake compared to those who learned about it through communication channels (x̄ = 1.79).

Those who learned about the earthquake through their work (x̄ = 1.96) reported taking more risks compared to those who received information through communication channels (x̄ = 1.56). Individuals who personally experienced the earthquake (x̄ = 3.04) expressed feeling more hypervigilant compared to those who learned about it through communication channels (x̄ = 2.62). Additionally, those who directly experienced the earthquake (x̄ = 2.59) reported more startle responses compared to those who learned about it through their work (x̄ = 2.20), from relatives (x̄ = 2.01), or from communication channels (x̄ = 1.90).

Those who directly experienced the earthquake (x̄ = 2.34) reported having greater difficulty concentrating compared to those who learned about it through communication channels (x̄ = 1.79). Additionally, individuals who experienced the earthquake themselves (x̄ = 2.46) reported more difficulty falling asleep or staying asleep compared to those who learned about it through communication channels (x̄ = 1.91) (Table 6).

The PCL-5 aggregates item scores to provide a continuous measure of PTSD symptom severity, encompassing symptom clusters and the disorder as a whole, akin to the PCL. These clusters include the re-experiencing (Criterion B) assessed by questions 1–5, each rated on a 4-point scale representing a total of 20 points. Avoidance behaviors (Criterion C) are measured by questions 6 and 7, totalling 8 points. Negative alterations in cognition and mood (Criterion D) are represented by 28 points, while hyperarousal (Criterion E) is defined by a total of 24 points. If the total score from this assessment exceeds 33, it indicates a clinical case necessitating treatment. Additionally, classifications based on the mean scores for each criterion are as follows: normal (x̄ ≥ 1.23), mild (1.23 < x̄ ≤ 1.64), moderate (1.64 < x̄ ≤ 2.455), severe (2.455 < x̄ ≤ 3.265), and extremely severe (x̄ > 3.265) (Table 3). These cutoff values were based on empirical scoring recommendations used in clinical research applying the PCL-5, including those by Weathers et al. (2018) [34], Bovin et al. (2016) [46], and Wortmann et al. (2016) [47], who suggested symptom severity classifications to support non-diagnostic interpretation and clinical screening in post-disaster settings. In this study, conducted with 619 participants, it was found that 191 participants scored 33 or higher, corresponding to 30.86% of the participants, indicating clinically significant PTSD symptoms (Figure 2). Among this group, 22 participants experienced symptoms at severe to extremely severe levels, while 19 participants exhibited extremely severe symptoms in at least one subscale. Additionally, three participants reported extremely severe symptoms across all four subscales, and nine participants showed extremely severe symptoms in three subscales.

When the earthquake experience of the search and rescue team is evaluated based on the four criteria, for those who directly experienced the earthquake, Criterion B (1.23 < x̄ ≤ 1.64) indicates a mild level of post-traumatic stress disorder. In contrast, those who learned about the earthquake through communication channels (1.64 < x̄ ≤ 2.455) are experiencing a moderate level of stress. While those who directly experienced the earthquake are similarly mildly affected in the other three criteria (C, D, and E), individuals who learned about the earthquake from their work, relatives, or communication sources are experiencing a moderate level of post-traumatic stress disorder in these criteria.

Considering the representation of the criteria with a violin plot (Figure 3), the average responses of participants to the questions (1–5) prepared for re-experiencing symptoms are in the moderate range, and the corresponding violin graphs show a more normal distribution compared to other criteria. A majority of participants (>75%) responded with scores between 0 and 2 for avoidance symptoms, and the averages show a significant increase up to level 4. In the category of negative alterations, 75% of participants scored below 1.6, with an average of 1.1, indicating a decrease in the number of individuals at risk for PTSD. For hyperarousal symptoms, the average is around 1.3, with 75% of participants scoring below the 1.8 average, and it is notably observed at the extremely severe level. These data help us understand the distribution and intensity of the symptoms.

Structural Equation Modelling of the Data

By using structural equation modelling (SEM), the relevant latent factors of post-traumatic stress disorder (PTSD) were subjected to regression analysis on PCL-5 items. SEM is based on the inclusion of multivariate statistical procedures that allow for modelling both observed or measured variables as well as latent factors. The latent factors considered here were re-experiencing, avoidance, negative alteration, and hyperarousal, and the measured variables were the twenty-items of PCL-5. This approach considers measurement errors and models complex relationships by creating a structural model that captures the underlying latent factors beneath multiple indicators [48]. An advantage of this approach is its ability to measure the amount of variance in indicators due to error or unreliability against the latent structure. Accounting for error variance mathematically generates highly reliable factors, thereby increasing the overall statistical power of the analysis.

The chi-square value obtained from the analysis conducted with LISREL is 687.54, with 164 degrees of freedom, resulting in a X²/df ratio of 4.19, indicating poor fit (4.19 > 3). Modifications were made and the value decreased to 2.96, resulting in an acceptable fit. The Root Mean Square Error of Approximation (RMSEA) has a moderate level of fit (0.0563), while the Normed Fit Index (NFI) indicates excellent fit (0.936). The Non-Normed Fit Index (NNFI) also shows excellent fit at 0.9447, and the Comparative Fit Index (CFI) indicates excellent fit at 0.9569. Additionally, the Root Mean Square Residual (RMR) has a moderate level of fit at 0.0518, and the Standardized Root Mean Square Residual (SRMR) shows an excellent level of fit at 0.0367, as seen in

Table 7. Fit indices of the model.

Compliance Indexes	Pre-Modification Values	Values After Modification	Compliance Criteria
X2/df 1	4.19	2.96	2 ≤ X2/df ≤ 3
RMSEA 2	0.0787	0.0563	0.05 ≤ RMSEA ≤ 0.08
NFI 3	0.8603	0.9368	0.90 ≤ NFI ≤ 0.95
NNFI(TLI) 3	0.8672	0.9447	0.90 ≤ NNFI(TLI) ≤ 0.95
CFI 3	0.8854	0.9569	0.90 ≤ CFI ≤ 0.95
RMR 2	0.2920	0.0518	RMR ≤ 0.08
SRMR 2	0.0705	0.0367	SRMR ≤ 0.08
AGFI 4	0.8459	0.9045	0.90 ≤ AGFI ≤ 1
GFI 3	0.8797	0.9327	0.90 ≤ GFI ≤ 0.95

¹ [45], ² [49], ³ [50], ⁴ [51].

. After evaluating the measurement model, the second step is to analyze the structural model, which assesses the relationship between indicators.

The process of path analysis according to the structural model allows for statistical testing of hypotheses [44]. As seen in Figure 4, the PTSD criteria and PCL-5 items are positively related (path coefficients: re-experience Q01:0.77, t01:21.08, Q02:0.75, t02:22.67, Q03:0.77, t03:23.57, Q04:0.64, t04:16.96, Q05:0.76, t05:19.95; avoidance Q06:0.82, t06:22.96, Q07:0.81, t07:22.85; negative alteration Q08:0.51, t08:12.42, Q09:0.57, t09:14.91, Q10:0.58, t10:15.09, Q11:0.74, t11:19.16, Q12:0.73, t12:20.40, Q13:0.76, t13:23.64 Q14:0.79, t14:22.75; and hyperarousal Q15:0.77, t15:20.34, Q16:0.60, t16:15.57, Q17:0.67, t17:18.18, Q18:0.79, t18:22.56, Q19:0.79, t19:23.82, Q20:0.71, t20:20.53).

Regarding normality of the data, it was observed that the data did not exhibit normal distribution. In the case of non-normally distributed, ordinal, or categorical data, the weighted least squares estimation method commonly used for predictions is employed. For this purpose, herein, analysis was conducted using the PLS-SEM toolbox software. When evaluating the obtained models, it was found that the Standardized Root Mean Square Residual (SRMR) value is less than 0.08, and the Indices of Tucker and Lewis (TLI) and Bentler and Bonett (NFI) values fall within the range of 0.95 ≤ NFI, TLI ≤ 1, indicating excellent fit (

Table 8. Model compliance values.

Models	SRMR	TLI	NFI
Composite Model	0.0633	0.8644	0.8390
Factor Model	0.0427	0.9662	0.9376

).

The first value examined in terms of convergent and discriminant validity is the alpha value. It is expected that this value should exceed 0.70 [52]. Upon examining the study data, it is observed that the alpha value meets this criterion. Another important value is Composite Reliability (CR). It is expected that this value should exceed 0.80 [53]. The study data indicate that the necessary conditions are met for this value as well. Another critical value is Average Variance Extracted (AVE). The AVE value should be greater than 0.50 [52], and the data in

Table 9. Convergent and discriminant validity.

Criteria	Cronbach Alpha	Average Variability Explained	Dillon–Goldstein Rho	Dijkstra–Henseler Rho
Re-experiencing	0.8573	0.6380	0.8978	0.8605
Avoidance	0.8034	0.8357	0.9105	0.8035
Negative Alteration	0.8471	0.5272	0.8849	0.8611
Hyperarousal	0.8626	0.5954	0.8977	0.8688

prove that this criterion has been met. Another important criterion is the Fornell–Larcker criterion, according to which each variable’s values should be higher than those of other variables [54] (

Table 10. Fornell–Larcker criterion.

Criteria	Re-Experiencing	Avoidance	Negative Alteration	Hyperarousal	AVE	FL Criterion
Re-experiencing	0	0.4478	0.4219	0.5427	0.6380	Satisfied
Avoidance	0	0	0.4516	0.3953	0.8357	Satisfied
Negative Alteration	0	0	0	0.6204	0.5272	Not Satisfied
Hyperarousal	0	0	0	0	0.5954	Satisfied

). This criterion has been met, as evidenced in the Table. Another essential condition to fulfil is factor loading values, which are presented in

Table 11. Item loadings.

Items	Re-Experiencing	Avoidance	Negative Alteration	Hyperarousal
Q01	0.8113
Q02	0.8313
Q03	0.8446
Q04	0.7238
Q05	0.7769
Q06		0.9149
Q07		0.9134
Q11			0.7507
Q12			0.766
Q13			0.8371
Q14			0.802
Q15				0.7647
Q16				0.6696
Q17				0.7296
Q18				0.8202
Q19				0.8448
Q20				0.7876

(Q08, Q09 and Q10 coded questions were excluded because they did not meet the necessary conditions for analysis).

.

The factor loadings of the variables are provided in Table 11. The authors of [52] state that factor loadings should be above 0.708. As evidenced in Table 11, all variable factor loadings exceed 0.708.

4. Discussion

Disasters cause individuals to unexpectedly lose their lives, homes, possessions, and close relationships, leaving deep psychological impacts [55]. Each person develops fundamental beliefs during childhood; these beliefs include assumptions that the world is a livable place, that people are generally well-intentioned and trustworthy, and that personal invulnerability exists [56]. However, traumatic events such as sudden disasters can shatter these fundamental beliefs, which is why disasters are often considered traumatic events [55]. The disruption of these core beliefs can lead individuals to face various psychological issues. The symptoms exhibited by workers as a result of secondary trauma are referred to as secondary traumatic stress symptoms [57]. These symptoms include re-experiencing traumatic events, heightened arousal, and avoidance behaviors [58]. Psychological resilience is defined as a personality trait that enables individuals to cope with stressful situations and continue with normal life routines [57]. Since the level of impact from traumatic events varies from person to person, it is important to compare the psychological resilience and secondary traumatic stress levels of disaster workers.

Recently, Türkiye experienced a doublet earthquake in its southern region on February 6, 2023. According to official reports, this devastating event resulted in the loss of over 50,000 lives and left more than 100,000 people injured. In response to this “disaster of the century,” a significant number of people (60,217) participated in rescue operations. In the present study, we aimed to evaluate the psychological status of 619 participants using the PCL-5 questionnaire. The findings revealed that experiencing the earthquake had a significant effect on post-traumatic stress symptoms, regardless of age, education, gender, or experience.

4.1. Gender Status of the Participants

As expected [59,60], women exhibited higher levels of post-traumatic stress than men. Reports suggest that this difference may be linked to hormonal fluctuations and structural as well as functional brain differences between the sexes, which can shape responses to trauma [61,62]. Greater emotional sensitivity and empathy may further amplify women’s susceptibility to traumatic stress. Higher prevalence rates of depression and anxiety among women compared to men also play a role in their trauma responses [63]. Moreover, societal gender roles and expectations, along with increased exposure to domestic violence, sexual harassment, and abuse, contribute to this heightened risk [58,64]. Additional factors, including economic hardship and social isolation, can exacerbate the psychological impact of trauma [65]. As will be discussed in relation to the other analyzed parameters, trauma responses—whether primary or secondary—are complex and warrant further investigation.

Whilst the present finding that women reported more severe PTSD symptoms across multiple domains is consistent with former studies, it can be acknowledged that such differences should be interpreted with caution [66]. Cultural and societal expectations in Türkiye, such as traditional gender roles and emotional expressiveness, may influence how trauma is experienced and reported. It is hypothesised that women may be more socially permitted or encouraged to acknowledge psychological distress, whereas men may under-report due to stigma or internalised norms of emotional suppression. Furthermore, caregiving responsibilities and emotional labour, which are often shouldered disproportionately by women in disaster contexts, may serve to exacerbate psychological vulnerability. These cultural dynamics emphasise the necessity of contextualised interpretations of gender differences in trauma responses [67,68].

4.2. Educational Status of the Participants

Among the analyzed parameters, the participants’ educational status appears critical in coping with post-traumatic stress [69]. Studies suggest that individuals with higher education levels generally possess stronger problem-solving skills, enabling them to analyze stressful situations more effectively and develop appropriate coping strategies [57,70]. This advantage is partly attributed to easier access to information and the ability to employ knowledge-based, solution-focused approaches [71]. Moreover, educated individuals often have greater professional experience and expertise, which can facilitate better stress management in the workplace. Research by Karanci and Rustemli [72] and Başoğlu et al. [73] indicates that lower education levels are associated with a higher risk of PTSD, whereas Gigantesco et al. [74] found no such relationship.

Interestingly, the present study revealed the opposite trend: participants with higher education levels were more affected and exhibited more severe post-traumatic stress symptoms. The reasons for this pattern are likely complex and multifactorial, involving psychological, sociocultural, and environmental factors [75]. As education increases, individuals may develop greater awareness of social injustices, societal challenges, and personal rights violations, which can intensify their perception of traumatic experiences [70]. Additionally, higher levels of empathy among educated individuals may cause them to internalize both their own and others’ traumatic experiences more deeply [76].

Overall, the present study reports that participants with higher education levels exhibited greater PTSD symptoms compared to those with lower education levels. While the mechanisms underlying this association remain unclear, previous studies suggest that individuals with higher education may have heightened awareness of disaster-related risks or greater empathic sensitivity, which could intensify emotional responses to trauma. However, further research is needed to clarify these relationships.

Contrary to the prevailing assumption that individuals with greater knowledge and experience would exhibit higher levels of resilience, our findings revealed a contradictory outcome [66]. Higher education has been demonstrated to exacerbate symptoms of post-traumatic stress disorder (PTSD) by increasing cognitive rumination, defined as the prolonged and repetitive consideration of traumatic events [67]. This is a compelling argument. Moreover, individuals with extensive experience frequently assume leadership roles, a situation which can engender heightened psychological distress through exposure to the trauma and moral injury experienced by others, in addition to an augmented responsibility for decision-making. The intensity of symptoms in this subgroup may also be influenced by secondary traumatization, defined as the accumulation of indirect trauma exposure over time [68].

4.3. Work Experiences of the Participants

Work experience generally provides practical advantages in managing and resolving stressful situations, as prior exposure can facilitate the development of effective coping strategies for similar events [77]. However, contrary to previous reports [78,79], participants with over 10 years of search and rescue experience in this study exhibited greater distress compared to those with less than 3 years of experience. Prolonged exposure to traumatic events may erode psychological resilience over time, as the accumulation of past traumas increases overall stress and vulnerability. Additionally, experienced rescue workers often face greater responsibilities and expectations, which can heighten both physical and psychological strain. When new traumatic events evoke memories of earlier experiences, these recollections can be reactivated, amplifying the emotional impact of the current event [75]. Such factors may explain why more experienced individuals in this study demonstrated greater susceptibility to trauma.

The observed non-linear relationship between professional experience and PTSD severity can be better understood through the lens of Cumulative Trauma Theory, which posits that repeated exposure to traumatic events can lead to a buildup of psychological burden, even in resilient individuals [80]. In accordance with this theory, experienced search and rescue workers may not only encounter a greater number of traumatic events over time, but also carry unresolved emotional residues from previous missions, which serve to amplify responses to new traumas.

Moreover, the Conservation of Resources (COR) Theory posits that psychological distress escalates in response to the perception of a threat to or actual loss of personal, social, or material resources [81]. In the case of highly experienced personnel, prolonged exposure has been shown to gradually deplete emotional reserves, social support, or a sense of efficacy, resulting in reduced coping capacity over time. This finding contributes to the understanding that greater experience does not necessarily guarantee greater resilience.

Furthermore, the Diathesis–Stress Model provides a framework for understanding individual variability in PTSD symptoms [82]. The model posits that individuals possess varying levels of vulnerability (diathesis), which interact with environmental stressors (e.g., exposure to disaster scenes) to determine psychological outcomes. Higher education and professional experience have been shown to correlate with increased cognitive processing, heightened awareness of responsibility, and leadership-related pressures. These factors have the potential to amplify stress reactions rather than mitigate them.

4.4. Age Status of the Participants

Age and its association with stress coping have been widely examined in previous studies. Older individuals are often considered more resilient due to greater life experience, whereas younger individuals tend to exhibit stronger post-traumatic stress responses, with lasting impacts on their development. In the present study, participants under 30 were more affected than those over 50. However, findings in the literature remain inconsistent. For instance, Cofini et al. [75] reported no significant relationship between age and PTSD, while other studies have identified age-related differences in post-traumatic stress responses [83,84,85].

4.5. Earthquake Exposure Status of the Participants

Direct exposure to a traumatic event places individuals at a higher risk of developing post-traumatic stress disorder (PTSD) [55]. Direct exposure refers to physically experiencing the event or being in immediate danger, while indirect exposure—such as learning about the event through news, social media, or testimonies—can also trigger post-traumatic stress symptoms [57]. Although indirectly exposed individuals do not experience the event first-hand, they may still be psychologically affected by its severity and impact. In the present study, search and rescue workers who were present during the earthquake reported greater distress than those who learned of the incident through communication channels before arriving on site. These findings align with the reports of Ursano et al. [55] and Van der Kolk et al. [86]. Conversely, Bryant and Harvey [87] found that the severity of physical injury does not predict post-traumatic stress levels, supporting previous research [88] indicating that trauma severity and stress response are not linearly related.

4.6. Sleep Status of the Participants

Regarding sleep patterns, younger participants (0–24 years) in this study reported more difficulty falling asleep or staying asleep compared to older age groups (40–49 years). These findings are consistent with those of Runtz and Schallow [56], who noted that younger and less experienced individuals have greater difficulty coping with stress. Additionally, trauma effects were more pronounced in female participants, particularly in the form of distressing recurrent dreams, feelings of detachment, sleep disturbances, and difficulty experiencing positive emotions. These results align with previous studies suggesting a higher risk of PTSD among women compared to men [89,90].

Analysis of responses related to re-experiencing, avoidance, negative alterations, and hyperarousal revealed that university graduates were 20% more likely than high school graduates to report reliving the earthquake and engaging in avoidance behaviors related to reminders of the event. Participants with a vocational school diploma reported a 27% greater sense of detachment from others compared to high school graduates. Furthermore, individuals with over 10 years of search and rescue experience reported reliving the earthquake 16% more intensely and exhibited 15% stronger physical reactions to reminders of the event compared to those with less than 3 years of experience.

Furthermore, this group exhibited a 14% greater frequency of avoidance behaviors related to memories and emotions associated with the earthquake, and a 13% higher likelihood of blaming themselves or others after stressful experiences. The research findings indicate that risk-taking behavior following an earthquake increases with the length of experience.

There may be a strong relationship between distressing dreams and trauma [91,92]. Individuals who have experienced trauma often have distressing dreams or nightmares in which they repeatedly relive traumatic events. These nightmares frequently involve re-experiencing the traumatic event and can lead to waking up with intense anxiety, fear, and panic [93]. Individuals with post-traumatic stress disorder (PTSD) commonly experience sleep disturbances, which can include difficulty falling asleep or staying asleep, often triggered by distressing dreams [94].

4.7. Structural Equation Modelling Findings

The SEM models obtained using both algorithms show a significant alignment between the tendency of earthquake search and rescue workers to re-experience trauma and avoidance. Previous research and theories suggest that avoidance symptoms are functionally intertwined with re-experiencing, as exposure to trauma-related stimuli is believed to minimize intense re-experiencing situations [95,96]. In accordance with those reports, our results revealed a moderate correlation (0.44) between these two factors (re-experiencing and avoidance). Similarly, there was a similar alignment between negative alteration and avoidance (0.45) as well as re-experiencing (0.42). In the case of research and rescue professionals, these findings may also reflect the impact of trauma on re-experiencing symptoms, but this still remains uncertain and, therefore, deserves to be investigated. In addition, it shows that there is no alignment between hyperarousal and negative alteration. According to the SEM analysis considered here, re-experiencing and avoidance are important predictors among post-earthquake trauma symptoms, but no other PTSD factor serves as a predictor. We further used the SEM model results prepared using the R 4.4.2 program for each question to confirm the regression among PTSD factors. Accordingly, it was observed that demographic data were quite effective in determining stress levels, but insufficient to provide a complete explanation (R², 5–10%). In this context, we need different independent variables, which may include whether search and rescue team employees engage in sports to reduce stress, their habits of playing musical instruments, regular vacation habits, their positions at work, income levels, and whether they have children.

Considering the magnitude of the problem, the prevalence of clinically significant PTSD symptoms observed in this study (30.86%) is relatively high compared to reports from other disaster contexts. For instance, Liao et al. (2002) [26] reported a PTSD prevalence of 16.4% among Taiwanese rescue workers within two months of a major earthquake. Following the 2011 Great East Japan Earthquake, Yokoyama et al. (2014) [97] documented PTSD rates ranging from 20% to 30% among first responders. Our findings are at the upper end of this range, which may reflect the exceptional severity and scale of the February 6, 2023, doublet earthquake, as well as the prolonged exposure and high mortality witnessed by Turkish search and rescue teams. These results highlight the critical need for systematic mental health interventions targeting disaster response personnel.

4.8. Highlights and Limitations

Following the doublet earthquakes, numerous studies have been conducted in geology and geophysics [98,99,100], and several reports have examined PTSD levels among local populations [101,102,103]. However, to date, no studies have specifically focused on post-traumatic stress disorder among search and rescue workers in Türkiye. The present study fills this gap by examining the psychological effects of the February 6, 2023 earthquake on a large sample of 619 search and rescue personnel. Findings related to gender, education, age, and direct earthquake exposure were largely consistent with previous reports, with the exception of work experience, where more experienced personnel showed greater distress.

Despite these contributions, this study has several limitations that should be acknowledged. First, its cross-sectional design captures PTSD symptoms at a single time point, limiting the ability to draw causal inferences or observe the progression of symptoms over time. Future longitudinal research is needed to examine how PTSD symptoms evolve and whether specific factors influence recovery or chronicity. Second, this study relied exclusively on self-report measures (PCL-5), which, while widely validated, are prone to recall bias, social desirability bias, and subjective misinterpretations of symptom severity. Clinical interviews or diagnostic assessments would provide a more robust evaluation of PTSD. Third, the generalizability of the findings is constrained, as the sample consisted solely of Turkish search and rescue workers (AFAD). Cultural, occupational, and contextual differences may limit the applicability of these results to other countries or disaster response groups. Moreover, the voluntary nature of participation may have introduced selection bias, with individuals experiencing either heightened or reduced stress being more likely to participate.

A further significant constraint is to the possibility of self-selection bias. The voluntary nature of participation may have resulted in an overrepresentation of people with either higher emotional awareness or more severe psychological problems, even if the response rate of 15.5% (619 out of 4000) is within acceptable bounds for online psychological surveys. This might affect how broadly the results can be applied to the larger group of SAR personnel participating in the earthquake response.

It is important to acknowledge the limitations of this study. Initially, the data were collected through self-report questionnaires, which may be subject to biases such as social desirability, over- or underreporting, and inaccurate introspection. Secondly, this study employed a cross-sectional design, which limits the ability to make causal inferences or observe changes in psychological symptoms over time. Thirdly, as the data were gathered approximately four months after the earthquake, participants’ recollections of their psychological responses may have been influenced by recall bias, potentially affecting the accuracy of symptom reporting. Fourthly, although the PCL-5 is a widely utilised and validated instrument for the assessment of PTSD symptoms, it remains a screening tool and does not supersede a formal clinical diagnosis by a mental health professional. Consequently, the prevalence and severity levels reported herein should be interpreted as provisional, not definitive. Finally, given that participation was voluntary, it is possible that individuals experiencing greater psychological distress or interest in the topic may have been more likely to respond, thus introducing a potential self-selection bias.

5. Conclusions and Recommendations

This study revealed that the traumatic effects of earthquakes on search and rescue workers vary considerably among individuals. Overall, experiencing an earthquake had a consistent impact on post-traumatic stress symptoms, regardless of age, education, gender, or experience. Women reported higher levels of post-traumatic stress than men, while participants with higher education levels exhibited greater stress symptoms compared to those with lower education levels. Similarly, workers with over 10 years of experience reported greater distress than those with less than 3 years of experience. Younger participants (under 30) were more affected than older ones (over 50). Moreover, teams present at the scene during the earthquake experienced greater distress than those who learned about the event through communication channels before arriving.

The social recovery process in the affected region is expected to take several years. Considering the long-term effects of the earthquake—such as reconstruction efforts, renewal of unsafe building stock, internal migration, rural development, and economic challenges—significant issues are likely to emerge nationwide. There is a pressing need for initiatives that preserve and enhance the mental health of professionals involved in disaster and emergency response. Providing psychological training before disasters can raise awareness of personal stress reactions, while programs aimed at strengthening psychological resilience may further improve coping capacity. During and after disaster operations, regular psychological briefings, support groups, and the involvement of social workers are essential. Approaches such as crisis intervention-focused group work and psychodrama techniques can be particularly effective. Additionally, developing social policies and legislation to safeguard the mental health of disaster workers remains a critical priority.

In light of the findings, several actionable implications are worth highlighting. First, search and rescue (SAR) teams should be routinely screened for PTSD symptoms using validated tools like the PCL-5 as part of post-disaster debriefing protocols. Early identification of individuals at risk could enable timely psychological intervention. Second, incorporating resilience training programs and psychological preparedness modules into SAR personnel training curricula may help build coping capacity before deployment. Third, establishing early intervention systems—including peer support networks and access to trauma-informed counseling—can mitigate the progression of distress symptoms. Finally, longitudinal monitoring of mental health outcomes should be integrated into disaster response strategies to track changes over time, assess intervention effectiveness, and ensure sustained psychological well-being among responders. These measures are crucial for maintaining both the effectiveness and the well-being of SAR personnel in future disaster scenarios.

The potential long-term effects of the earthquakes, which have yet to fully emerge, must be taken into account. Addressing these challenges requires adequate resources, strong motivation, and sustained institutional commitment. The experiences from this disaster underscore the need for Türkiye to strengthen its resilience and capacity to withstand future large-scale earthquakes. Implementing a comprehensive, long-term disaster management strategy and sustainable development plans is essential. These strategies should focus not only on physical reconstruction but also on restoring the social and economic fabric. Enhancing institutional structures, raising disaster awareness, and ensuring the active participation of all societal sectors will better prepare Türkiye for future disasters.